Staff Machine Learning Engineer

Bellevue · Dallas · New York City · Santa Clara · New Jersey · USD 152,000-190,000 · 2+ years experience · Posted Sep 30, 2026

At a glance

We are looking for a Machine Learning Engineer to join our Artificial Intelligence Guard team in a remote capacity within the United States (with a hybrid preference for Santa Clara, CA), reporting directly to the Director of AI and Machine Learning Engineering team.
Operating at the core of the team that built the world’s largest cloud security platform processing over 400 billion transactions daily, you will design, build, and deploy end-to-end machine learning pipelines while integrating advanced AI capabilities into production-ready SaaS offerings to directly impact our global strategic roadmap.

Build and deploy end-to-end ML pipelines spanning data curation, training/fine-tuning, evaluation, and high-scale serving
Develop deep learning models for security use cases, including transformer-based classifiers, embedding models, and sequence modeling across high-volume traffic data
Adapt, fine-tune, and productionize open-weight LLMs and small language models using techniques such as LoRA/QLoRA, instruction tuning, and distillation
Optimize models for production through quantization, batching, and high-throughput serving with frameworks like Hugging Face, PEFT, vLLM, TensorRT-LLM, and ONNX Runtime to balance latency, cost, and quality
Architect and operationalize robust ML services across cloud platforms (AWS, GCP) leveraging cloud-native microservice architectures

Demonstrated experience utilizing modern AI/ML frameworks and foundational model workflows to design, train, and deploy intelligent systems at scale
Bachelor's or advanced degree in Computer Science, Machine Learning, Mathematics, Physics, Statistics, Engineering, or a related field, with 2+ years of applied ML experience
Solid grounding in machine learning fundamentals, including loss functions, optimization, regularization, evaluation metrics, and handling imbalanced or noisy data
Strong Python programming expertise and hands-on experience with modern deep learning frameworks such as PyTorch, TensorFlow, or JAX
Proven experience training/fine-tuning large language models (LLMs) and deploying deep learning models (e.g., transformers, embedding models, generative AI architectures etc) in production environments
Ability to work with large-scale datasets, write clean, testable code, and operate with high autonomy on ambiguous technical challenges

Proven experience developing generative AI architectures or building scalable inference optimization pipelines
Peer-reviewed publications or prominent open-source contributions demonstrating depth in modern deep learning techniques (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, IEEE)

Remote capacity within the United States with a hybrid preference for Santa Clara, CA